Obstructive sleep apnea after myocardial infarction.

(1)

[2] Compton PA, Zankar AA, Adesanya AO, Banerjee S, Brilakis ES. Risk of noncardiac surgery after coronary drug-eluting stent implantation. Am J Cardiol 2006;98: 1212–3.

[3] Schouten O, Bax JJ, Poldermans D. Management of patients with cardiac stents undergoing noncardiac surgery. Curr Opin Anaesthesiol 2007;20:274–8.

[4] Godet G, Le Manach Y, Lesache F, Perbet S, Coriat P. Drug-eluting stent thrombosis in patients undergoing non-cardiac surgery: is it always a problem? Br J Anaes 2008;100:472–7.

[5] Coats AJ. Ethical authorship and publishing. Int J Cardiol 2009;131:149–50.

Obstructive sleep apnea after myocardial infarction

Stefano Fumagalli

a,

⁎

, Francesca Tarantini

a

, Chiara Cipriani

a

, Marta Casalone Rinaldi

a

, Sanja Jelic

b

,

Sara Francini

a

, Yasmine Makhanian

a

, Margherita Padeletti

a

, Luigi Padeletti

c

, Niccolò Marchionni

a

a_{Department of Critical Care Medicine and Surgery, Gerontology and Geriatric Medicine, Intensive Care Unit, University of Florence and AOU Careggi, Florence, Italy} b_{Division of Pulmonary, Allergy, and Critical Care Medicine, Columbia University College of Physicians and Surgeons, New York, NY, USA}

c

Department of Critical Care Medicine and Surgery, Internal Medicine and Cardiology Unit, University of Florence and AOU Careggi, Florence, Italy

a r t i c l e i n f o

Article history:

Received 27 March 2010

Received in revised form 21 April 2010 Accepted 29 April 2010

Available online 1 June 2010

Keywords:

ECG Holter monitoring Heart rate variability Myocardial infarction Obstructive sleep apnea Ventricular arrhythmias

Obstructive sleep apnea (OSA) is a risk factor for hypertension,

myocardial ischemia and stroke, and is associated with increased

mortality

[1,2]

. Hypoxia-induced activation of the sympathetic

nervous system, in

_{ﬂammation and oxidative stress contribute to}

increase cardiovascular risk in patients with sleep disturbances

[2

–4]

.

The present study was aimed at evaluating the prevalence of OSA after

a recent myocardial infarction (MI) and de

ﬁning its clinical predictors.

All patients with recent MI (median time from symptoms onset:

32 days), admitted to our cardiac rehabilitation center between March

2007 and December 2008, were enrolled in the study. All subjects

were in stable clinical conditions.

At baseline, patients underwent echocardiogram, ECG Holter,

ergometric stress test, and blood tests. Ventricular arrhythmia risk

pro

ﬁle was quantiﬁed on ECG Holter analysis, using the Lown and

Wolf classi

ﬁcation: frequent (N30/h) and complex (presence of

couplets and tachycardia) arrhythmias

[5]

. Frequent supraventricular

arrhythmia was de

ﬁned as a number of ectopic beats N30/h. The peak

CPK-MB and Troponin I values detected during acute MI were

registered.

The presence of OSA was assessed by ECG Holter recording using

a validated software (Lifescreen Apnea; SPACELABS Healthcare

—

Issaquah, Washington, USA and Hertford, UK) integrated in the

Impresario Holter Analysis System (Symphony model; SPACELABS

Healthcare). Brie

ﬂy, the continuous change from airways obstruction

to normal air

ﬂow determines a shift from sympathetic to

para-sympathetic dominance, with related changes in heart rate. The

software analyzes modi

ﬁcations in heart rate variability (HRV) and in

QRS amplitude, returning the mean apnea-hypopnea index (AHI)

[6,7]

. Diagnostic sensitivity of this technique, compared to

polysom-nography, is 90%

[6,7]

. ECG Holter recorders had a sampling rate of

2048 Hz (EVO recorder; SPACELABS Healthcare). Patients were

strati

_{ﬁed on AHI values into three groups: normal (AHI≤5), mild}

(AHI 5

–15) and moderate-severe apnea (AHIN15)

[1,2]

. Two

para-meters of HRV in time domain analysis were evaluated, SDNN (the

standard deviation of RR intervals of the ECG Holter recording) and

RMSSD (the square root of the mean squared differences of successive

RR intervals), corresponding to sympathetic and parasympathetic

activity

— the former, and to parasympathetic activity only — the latter

[8]

.

Exclusion criteria for the study were: dominant non-sinus rhythm;

presence of an implanted pacemaker; frequent artifacts in the ECG

Holter recording; diabetes mellitus type 1 and other conditions

associated with a severe autonomic dysfunction.

Each patient gave written informed consent to the study; the

protocol conforms to the ethical guidelines of the 1975 Declaration of

Helsinki.

Continuous and categorical variables were expressed as mean ±

standard deviation (SD) and percentages, respectively. For continuous

variables, Student's t test or analysis of variance were employed to

compare two or more groups of subjects. When the variables were not

normally distributed, non parametric tests were employed. The

association between two continuous variables was assessed with

linear regression analysis. Differences in categorical variables

dis-tribution were evaluated with

χ

2

_test.

To identify the clinical predictors of OSA, those factors correlated to

this condition in univariate analysis, were entered into a multivariate

linear regression model.

We enrolled 191 patients (

Table 1

), 73% after a ST-elevation MI

(STEMI). Primary percutaneous coronary intervention was performed

in 84% of cases. Mean peak values of CPK-MB and troponin I were

113 UI/L (25th

–75th percentile: 38–145 UI/L) and 106 ng/mL (25th–

75th percentile: 16

–141 ng/mL), respectively (

Table 2

).

The maximum workload attained at the baseline ergometric

stress test was 118 ± 40 Watt. The test was suggestive of myocardial

ischemia only in 18 patients (9.4%).

ECG Holter recordings had a mean length of 22:09 ± 1:27 h. Mean

heart rate was 66 ± 9 b/min. SDNN and RMSSD were within lower

normal limits (

Table 2

). Second or third degree atrioventricular blocks

were absent, cardiac pauses longer than 2 s were present only in 7

⁎ Corresponding author. Department of Critical Care Medicine and Surgery, Intensive

Care Unit, Gerontology and Geriatric Medicine, University of Florence and AOU Careggi, Via delle Oblate, 4-50141-Florence, Italy. Tel.: +39 055 4271471; fax: + 39 055 4271469.

E-mail address:fumadue@tin.it(S. Fumagalli).

(2)

patients (3.7%). ST segment depression was observed in 6 patients

(3.1%).

Mean sleep time was 7:56 ± 1:13 h; 143 subjects (74.9%) had AHI

scores

N5, with a mean value of 17.7±10.8 (mild: N=67, 35.3%;

moderate-severe apnea: N = 76, 40.1%).

Body weight correlated directly with AHI (

Table 3

), with the

highest value observed in moderate-severe apnea patients (normal:

75 ± 13 kg, mild: 74 ± 11 kg, moderate-severe apnea: 80 ± 12 kg;

p = 0.029).

Uncontrolled hypertension (i.e. blood pressure

N130/80 mmHg at

the time of enrollment), was positively associated with AHI. AHI

linearly increased with uric acid and CPK-MB plasma concentrations,

and RBC count (

Table 3

). While patients with STEMI displayed higher

values of AHI (

Table 3

), no relation was found with residual LVEF

(p = 0.536) (

Table 3

). Complex ventricular arrhythmias directly

cor-related with AHI (

Table 3

), with the highest prevalence of frequent

ventricular arrhythmias in the moderate-severe group (normal: 12.5%,

mild: 18.8%, moderate-severe apnea: 68.8%; p = 0.033).

The multivariate linear regression analysis con

ﬁrmed the direct

correlation of AHI with body weight, RBC count, use of K

+

_sparing

agents, presence of uncontrolled hypertension and complex

ventri-cular arrhythmias (

Table 4

).

This study suggests that OSA is highly prevalent in patients with a

recent MI. The study was conducted 4 weeks after MI to exclude

possible confounders, such as acute in

ﬂammation and overt left

ven-tricular failure. CPK-MB peak plasma concentration and STEMI, two

indicators of MI extension, correlated with the severity of OSA.

Fur-thermore, K

+

_{sparing agents, more frequently prescribed in patients}

with moderate-severe left ventricular dysfunction (p

b0.001), were

associated with greater AHI. A strong relation was found between OSA

and RBC count, corroborating previous reports of a predictive value of

hemoglobin and hematocrit for the presence of sleep disturbances

[9]

.

The correlation between AHI and plasma levels of uric acid, possibly

related to enhanced ATP transformation, may suggest tissue distress

[10]

.

Table 1

Clinical characteristics of patients.

Range Age (years) 62 ± 13 28–94 Men (%) 81.7 Weight (kg) 77 ± 13 47–115 BMI (kg/m2 ) 26.6 ± 3.5 16.3–40.2 Smokers Current (%) 21.6 Past (%) 51.1 Comorbidities COPD (%) 7.9 Diabetes (%) 15.3 Dyslipidemia (%) 45.0 Hypertension (%) 56.3 Previous MI (%) 8.7 Stroke/TIA (%) 3.6

Valvular heart diseases

Aortic insufﬁciency (%) 3.2 Aortic stenosis (%) 10.2 Mitral insufﬁciency (%) 9.7 Blood tests Creatinine (mg/dL) 0.95 ± 0.24 0.50–2.00 ESR (mm/h) 27.2 ± 20.1 2.0–111.0 Hemoglobin (g/dL) 13.5 ± 1.4 10.0–16.4 RBC count (106 /mm3 ) 4.6 ± 0.5 3.4–7.0 Uric acid (mg/dL) 5.9 ± 1.3 2.0–9.7

BMI: body mass index; CABG: coronary artery bypass graft; COPD: chronic obstructive pulmonary disease; ESR: erythrocyte sedimentation rate.

Table 2

Cardiological characteristics of patients and drug therapy.

Range Type of myocardial infarction

Anterior STEMI (%) 36.6

Inferior STEMI (%) 36.6

NSTEMI (%) 26.8

Primary PCI site

Left main (%) 0.5

Left anterior descending (%) 41.7

Circumﬂex (%) 12.3 Right CA (%) 29.4 No PCI (%) 16.0 LVEF (%) 52 ± 11 20–74 Preserved (%) 62.4 Mild reduction (%) 19.4 Moderate/severe reduction (%) 18.2

ECG Holter monitoring

Frequent SV arrhythmias (%) 4.7 Frequent V arrhythmias (%) 8.4 Complex V arrhythmias (%) 36.6 SDNN (ms) 116 ± 34 37–222 RMSSD (ms) 33 ± 20 10–128 Drug therapy ASA (%) 96.9 Clopidogrel (%) 95.3

ACE inhibitors/ATII antagonists (%) 94.8

β-blocking agents (%) 89.5

Statins (%) 93.2

K+

sparing agents (%) 14.7

Diuretics (%) 22.5

AT: angiotensin; CA: coronary artery; LVEF: left ventricular ejection fraction — categorized as normal (N50%), mildly (41–49%), moderately (26–40%), and severely (b25%) depressed; MI: myocardial infarction; PCI: percutaneous coronary intervention; RMSSD: root mean square of the squared difference between consecutive RR intervals; SDNN: standard deviation of all RR intervals of the ECG Holter recording; STEMI/ NSTEMI: ST-/non-ST-elevation MI; SV/V: supraventricular/ventricular.

Table 3

Univariate analysis of apnea-hypopnea index by clinical variables.

Condition p − + Men 8.0 ± 6.9 15.2 ± 11.8 b0.001 Present smokers 13.7 ± 11.4 14.8 ± 11.8 0.584 COPD 14.0 ± 11.6 13.6 ± 10.0 0.893 Diabetes 13.7 ± 11.6 15.3 ± 11.7 0.907 History of hypertension 13.4 ± 10.8 14.4 ± 12.0 0.551 Uncontrolled hypertension 12.5 ± 10.2 16.1 ± 13.1 0.039 Stroke/TIA 14.1 ± 11.6 9.1 ± 8.4 0.293 Aortic insufﬁciency 13.6 ± 11.6 22.8 ± 8.3 0.055 Aortic stenosis 14.1 ± 11.5 13.6 ± 12.1 0.868 Mitral insufﬁciency 14.2 ± 11.6 13.3 ± 11.4 0.515 Frequent SV arrhythmias (%) 14.4 ± 11.5 5.5 ± 6.1 0.023 Complex V arrhythmias (%) 12.5 ± 10.2 16.2 ± 13.0 0.029 STEMI 11.6 ± 10.6 15.0 ± 11.8 0.049

ACE inhibitors/AT II antagonists 19.9 ± 11.9 13.6 ± 11.4 0.092

β-blocking agents 15.1 ± 15.8 13.8 ± 10.9 0.623 Statins 12.5 ± 15.1 14.1 ± 11.2 0.645 K+_{sparing agents} _{13.3 ± 11.0} _{18.1 ± 13.6} _0.048 Diuretics 14.5 ± 12.0 12.0 ± 9.4 0.206 β±se R p Age (Δ·year) / 0.035 0.633 Weight (Δ·kg) 0.23 ± 0.07 0.243 0.001 BMI (Δ·kg/m2 ) / 0.138 0.059 CPK MB (Δ·UI/L) 0.04 ± 0.01 0.364 0.001 Creatinine (Δ·mg/dL) / 0.108 0.148 ESR (Δ·mm/h) / 0.077 0.299 Hemoglobin (Δ·g/dL) / 0.138 0.062 RBC count (Δ·106_/mm3₎ _{3.8 ± 1.5} _0.179 _0.015 Uricemia (Δ·mg/dL) 1.5 ± 0.7 0.159 0.032 HR (Δ·b/min) / 0.032 0.661 SDNN (Δ·ms) / 0.117 0.111 RMSSD (Δ·ms) / 0.133 0.071

`Uncontrolled hypertension: blood pressureN130/80 mmHg at baseline evaluation; SV/V: supraventricular/ventricular; Δ: AHI changes per unitary change of the independent variable. Variables represented in less than 5% of the study population were excluded from the analysis.

551 Letters to the Editor

(3)

Table 4

Clinical predictors of apnea–hypopnea index by multivariate linear regression analysis (R = 0.435, pb0.001). β±se 95%CI p Body weight (Δ·Kg) 0.2 ± 0.1 0.1–0.3 0.001 RBC count (Δ·106 /mm3 ) 3.0 ± 1.5 0.1–5.8 0.043

Complex V arrhythmias (yes vs. no) 3.5 ± 1.6 0.3–6.8 0.030 Frequent SV arrhythmias (yes vs. no) −9.5±3.7 −(16.7–2.3) 0.010 Uncontrolled hypertension (yes vs. no) 4.2 ± 1.6 1.0–7.4 0.011 K+

sparing agents (yes vs. no) 5.2 ± 2.3 0.7–9.8 0.024

Constant −20.1±8.0 −(35.9–4.4) 0.013

Δ: AHI changes per unitary change of the independent variable; RBC: red blood cell; SV/ V: supraventricular/ventricular.

The association between AHI and complex ventricular arrhythmias

is an important novel

_{ﬁnding. In the Sleep Heart Health Study, the}

presence of a sleep disturbance, increased about three times the risk to

develop a not sustained ventricular tachycardia, and at least two times

the risk to experience complex ventricular arrhythmias

[11]

. The

correlation between OSA and ventricular arrhythmias might be

explained by several factors, including increased left ventricular

afterload with consequent reduction in preload, increased

sympa-thetic out

ﬂow, and the possible presence of diastolic dysfunction

[12]

.

Few limitations of the study need to be acknowledged. Only 2

patients reported the use of a CPAP previous to the occurrence of MI,

but we cannot rule out the possibility that subclinical sleep

dis-turbances might have been present before the acute event in a portion

of our population. The technique we used to detect OSA, even if

validated, employs only the electrocardiographic dimension of the

polysomnography study. It is known that a recent MI may reduce HRV

in

ﬂuencing the ability of ECG analysis to detect sleep apnea. However,

HRV recorded in our study population was still within normal limits

[8]

; moreover, a reduction of HRV should determine an

under-estimation of the prevalence of sleep disturbances. Furthermore, a

recent Scienti

ﬁc Statement on sleep apnea and cardiovascular disease,

recommended to adopt new non-invasive tools of screening, less

expensive and more widely applicable than standard

polysomnogra-phy

[1]

.

In conclusion, previously unrecognized OSA is highly prevalent

among patients with recent MI and associates with increased body

weight, uncontrolled hypertension and complex ventricular

arrhyth-mias. Clinicians should seek and treat sleep disturbances when

occurring in patients with recent MI.

Con

ﬂict of interest

None to disclose.

We thank Aldo Europei, Luigi Garuglieri, and Alberto Nincheri

(ESAOTE SpA, Florence, Italy) and SPACELABS Healthcare

— Issaquah,

Washington, USA and Hertford, UK, for technical support.

The authors of this manuscript have certi

ﬁed that they comply

with the Principles of Ethical Publishing in the International Journal of

Cardiology

[13]

.

References

[1] Somers VK, White DP, Amin R, et al. Sleep apnea and cardiovascular disease. An American Heart Association/American College of Cardiology Foundation Scientiﬁc Statement From the American Heart Association Council for High Blood Pressure Research Professional Education Committee, Council on Clinical Cardiology, Stroke Council, and Council on Cardiovascular Nursing. Circulation 2008;118:1080–111. [2] Bradley TD, Floras JS. Obstructive sleep apnoea and its cardiovascular

conse-quences. Lancet 2009;373:82–93.

[3] Somers VK, Dyken ME, Clary MP, Abboud FM. Sympathetic neural mechanisms in obstructive sleep apnea. J Clin Invest 1995;96:1897–904.

[4] Quan SF, Gersh BJ. Cardiovascular consequences of sleep-disordered breathing: past, present and future: report of a workshop from the national center on sleep disorders research and the national heart, lung, and blood institute. Circulation 2004;109:951–7.

[5] Lown B, Wolf M. Approaches to sudden death from coronary heart disease. Circulation 1971;44:130–42.

[6] Penzel T, McNames J, Murray A, de Chazal P, Moody G, Raymond B. Systematic comparison of different algorithms for apnoea detection based on electrocardio-gram recordings. Med Biol Eng Comput 2002;40:402–7.

[7] de Chazal P, Heneghan C, Sheridan E, Reilly R, Nolan P, O'Malley M. Automated processing of the single-lead electrocardiogram for the detection of obstructive sleep apnoea. IEEE Trans Biomed Eng 2003;50:686–96.

[8] Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability: standards of measurement, physiological interpretation, and clinical use. Circulation 1996;93:1043–65. [9] Zilberman M, Silverberg DS, Bits I, et al. Improvement of anemia with

erythropoietin and intravenous iron reduces sleep-related breathing disorders and improves daytime sleepiness in anemic patients with congestive heart failure. Am Heart J 2007;154:870–6.

[10] Braghiroli A, Sacco C, Erbetta M, Ruga V, Donner CF. Overnight urinary uric acid: creatinine ratio for detection of sleep hypoxemia. Validation study in chronic obstructive pulmonary disease and obstructive sleep apnea before and after treatment with nasal continuous positive airway pressure. Am Rev Respir Dis 1993;148:173–8.

[11] Mehra R, Benjamin EJ, Shahar E, et al. Association of nocturnal arrhythmias with sleep-disordered breathing: the sleep heart health study. Am J Respir Crit Care Med 2006;173:910–6.

[12] Arias MA, Sanchez AM. Obstructive sleep apnea and its relationship to cardiac arrhythmias. J Cardiovasc Electrophysiol 2007;18:1006–14.

[13] Coats AJ. Ethical authorship and publishing. Int J Cardiol 2009;131:149–50.